Title :
A hybrid method for Heart Rate Variability analysis
Author :
Bouziane, Ahmed ; Yagoubi, Benabdellah ; Malika, Mimi
Author_Institution :
Electr. Eng. Dept., Univ. of Mostaganem, Algeria
Abstract :
Heart Rate Variability (HRV) signals, derived from an Electrocardiogram signal (ECG), are strongly related to the activity of the Autonomous Nervous System (ANS). This paper suggests the new estimation technique to calculate the duration of the two activities of ANS (Sympathetic and Parasympathetic). The signal HRV is, naturally, non stationary because of the non steady state of the sympathetic and parasympathetic behaviour. The proposed method is, therefore, based on dividing this signal into stationary segments to obtain steady states. Each temporal segment is represented by a Gaussian white noise whose variance is also its Power Spectral Density (PSD). The results obtained, in this work, allows to localize as well as, more importantly, to estimate the dominance duration of either the sympathetic or the parasympathetic activities during the test, as result of this, we can calculate the duration of a person´s stress in sensitive situations.
Keywords :
Gaussian noise; electrocardiography; estimation theory; medical signal processing; neurophysiology; white noise; ECG; Gaussian white noise; autonomous nervous system; electrocardiogram signal; estimation technique; heart rate variability signal analysis; parasympathetic ANS; person stress; power spectral density; signal HRV; stationary segments; sympathetic ANS; temporal segment; Estimation; Heart rate variability; Interpolation; Resonant frequency; Spectral analysis; Time-frequency analysis; FFT; Gaussian approximation; Welch´s method; heart rate variability; interpolation; non stationary signal;
Conference_Titel :
Advanced Technologies for Signal and Image Processing (ATSIP), 2014 1st International Conference on
Conference_Location :
Sousse
DOI :
10.1109/ATSIP.2014.6834626